About

Sharandeep Singh Handa is a skilled Data Science Enthusiast with over 4 years of demonstrated experience in working for Fortune 500 companies, helping them solve complex business problems. Currently working as a Business Intelligence Engineer at Amazon, Sharandeep is recognized for his ownership and commitment towards work. Sharandeep's skill set includes Descriptive and Predictive Analytics, Data Sciences, Data Modelling, Enterprise Data Warehousing, ETL and ELT Designs, DevOps, and Business Intelligence tools. He has experience in communicating and presenting to various levels of business stakeholders. Before joining Amazon, Sharandeep worked as a Senior Data Scientist at Enquero and as a Decision Scientist at Mu Sigma. At Mu Sigma, he contributed to the migration of deployment servers for a three-tier web application from on-premise OpenStack servers to Azure Cloud, helping the company increase its user-base by ~ 15% with a drop in latency and data loading time for the targeted users. He projected a strategy for application server migration to Azure, with defined advantages of Azure cloud over on-premise OpenStack servers. He employed ~ 200 VM's on various availability zones to increase the user-base of the application, using OneOps. He discovered an increase in active user count by ~ 15% post deploying the web application to Azure Cloud. He also created data load scripts for populating data of ~ 45 tables in SAP HANA from Hadoop, to incorporate change in the source of data. He designed ETL workflow for Summary Tables by collating data from ~ 20 base tables to populate KPI’s for stores across regions. Sharandeep's education background includes a Post Graduate Diploma in Machine Learning and AI from IIIT Bangalore, a Bachelor's degree in Electronics and Communications Engineering from VIT, and Higher Secondary and Secondary Education from Sri Chaitanya Junior College and Atomic Energy Central Schools, respectively. Sharandeep's tech stack includes Data Scientist, SQL, ETL, Python, Azure, ML, Research Scientist, Hadoop, DevOps, Web, Data Engineering, Jupyter, Reinforcement Learning, Deep Learning, NLP, Data Warehouse, Big Data, Django, Docker, Neural Networks, Jenkins, Backend, and Apache Hive.